Mika Hämäläinen

626 citations
58 papers · 216 indexed · h-index 8
Topics
Natural Language Processing Techniques (30 papers)Topic Modeling (23 papers)Lexicography and Language Studies (8 papers)
Journals
SHILAP Revista de lepidopterologíaLanguage Resources and EvaluationEuropean Journal of Sport Science

In The Last Decade

Mika Hämäläinen

50 papers receiving 164 citations

Peers

Mika Hämäläinen
Comparison fields: 5 of 57
  • Artificial Intelligence 145
  • Sociology and Political Science 49
  • Language and Linguistics 31
  • Social Psychology 19
  • Literature and Literary Theory 14
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Citations per field
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Citations per year

Countries citing papers authored by Mika Hämäläinen

Since Specialization
Citations

This map shows the geographic impact of Mika Hämäläinen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mika Hämäläinen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mika Hämäläinen more than expected).

Fields of papers citing papers by Mika Hämäläinen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mika Hämäläinen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mika Hämäläinen. The network helps show where Mika Hämäläinen may publish in the future.

Co-authorship network of co-authors of Mika Hämäläinen

This figure shows the co-authorship network connecting the top 25 collaborators of Mika Hämäläinen. A scholar is included among the top collaborators of Mika Hämäläinen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mika Hämäläinen. Mika Hämäläinen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 2
3 1
4 1
5 4
6 2
7
The Great Misalignment Problem in Human Evaluation of NLP Methods
2
8 0
9 1
10 1
11 5
12 1
13 7
14 2
15
Modelling the Socialization of Creative Agents in a Master-Apprentice Setting: The Case of Movie Title Puns
4
16 19
17
Morphosyntactic Disambiguation in an Endangered Language Setting
2
18
Advances in Synchronized XML-MediaWiki Dictionary Development in the Context of Endangered Uralic Languages
5
19
Extracting a Semantic Database with Syntactic Relations for Finnish to Boost Resources for Endangered Uralic Languages
5
20
Combining Concepts and Their Translations from Structured Dictionaries of Uralic Minority Languages
2

About Mika Hämäläinen

Mika Hämäläinen is a scholar working on Artificial Intelligence, Language and Linguistics and Linguistics and Language, having authored 58 papers that have together received 216 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (30 papers), Topic Modeling (23 papers) and Lexicography and Language Studies (8 papers). The work is most often cited by research in Artificial Intelligence (145 citations), Language and Linguistics (31 citations) and Communication (11 citations). Mika Hämäläinen has collaborated with scholars based in Finland, United Kingdom and Mongolia. Frequent co-authors include Silvia Camporesi, Tanja Säily, Eetu Mäkelä, Jörg Tiedemann, Philippe Pasquier, Timo Honkela, Shuo Zhang, Terttu Nevalainen, Trond Trosterud and Mikko Tolonen. Their work appears in journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation and European Journal of Sport Science.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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